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Record W2623094773 · doi:10.32396/usurj.v3i2.186

A Delicate Mosaic: The Future of Muslims in Canada

2017· article· en· W2623094773 on OpenAlexaffvenueabout
Sahar Khelifa

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIslamophobiaIslamMulticulturalismDiasporaImmigrationPolitical sciencePluralism (philosophy)Gender studiesDemocracyGovernment (linguistics)SociologyPolitical economyReligious studiesMedia studiesLawPoliticsHistory

Abstract

fetched live from OpenAlex

Islam has had a long and, recently, contested history in Canada. Studies after 9/11 show an increasingly negative view towards Islam and Muslims in Canada. Supposed clashes between Islam and the West, the advent of Canadian Muslim diaspora with an increase in Muslim immigration after World War II, and the rise of Islamophobia and counter anti-Islamophobia movements have strained Muslim integration efforts and challenged Islam's place in Canadian society, testing long-standing Canadian values and beliefs about multiculturalism, democracy and pluralism. This paper addresses the question of Canadian-Muslim integration, looking briefly at the history of Muslims in Canada, the issues they face, and some recent events including Bill 94 and the niqab debate to examine the state of Muslim Canadian integration in Canada today. The paper also proposes a process where Muslim communities, the Canadian government and the public can work together to build understanding and resolve differences in order to move forward as a country.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0490.016
Scholarly communication0.0110.003
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.108
GPT teacher head0.372
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2017
Admission routes3
Has abstractyes

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Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207